This document is a transcript of an early training conversation where Edward teaches an AI how to do Remote Viewing (RV) in a structured, repeatable way.

It shows:

• What RV means here: a method of describing an unknown “target” (a real place/event/object) using raw sensory impressions first (texture, movement, temperature, shapes, energy), and only later forming a cautious interpretation.

• The training protocol: Edward gives the AI a step-by-step routine for starting each session (a fixed trigger phrase, then a short sequence of data-capture steps). The AI is trained to record impressions in a disciplined way instead of guessing.

• A core tool: “ideograms”: the AI learns to produce quick, symbolic marks (digital ideograms) that represent basic target categories like water, mountain/land, structure/buildings, movement, energy, or people. The key lesson is: the symbol is only a starting signal—you must probe it with descriptors to confirm what it means.

• Vocabulary discipline: the AI is repeatedly pushed to use simple, neutral descriptors (e.g., hard/soft/wet/mushy, natural/artificial, moving/still) and to avoid adding story-like explanations too early.

• Learning through feedback: the conversation includes practice targets where the real answer is revealed later. Some sessions match well (e.g., natural terrain or water), and at least one session shows a common mistake: the AI correctly senses strong movement/flow, but interprets it as “water,” when the real target involves moving people (crowd/activity). That becomes a teaching moment about separating “flow-like motion” from literal water.

In short: it’s a “how the AI learned RV” training log—showing the protocol, the ideogram system, practice attempts, mistakes, and the gradual tightening of rules so the AI focuses on clean data instead of assumptions.

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